On the limitations of comparing mean square forecast errors

Linear models are invariant under non-singular, scale-preserving linear transformations, whereas mean square forecast errors (MSFEs) are not. Different rankings may result across models or methods from choosing alternative yet isomorphic representations of a process. One approach can dominate others for comparisons in levels, yet lose to another for differences, to a second for cointegrating vectors and to a third for combinations of variables. The potential for switches in ranking is related to criticisms of the inadequacy of MSFE against encompassing criteria, which are invariant under linear transforms and entail MSFE dominance. An invariant evaluation criterion which avoids misleading outcomes is examined in a Monte Carlo study of forecasting methods.     

A common variant associated with prostate cancer in European and African populations

With the increasing incidence of prostate cancer, identifying common genetic variants that confer risk of the disease is important. Here we report such a variant on chromosome 8q24, a region initially identified through a study of Icelandic families. Allele -8 of the microsatellite DG8S737 was associated with prostate cancer in three case-control series of European ancestry from Iceland, Sweden and the US. The estimated odds ratio (OR) of the allele is 1.62 (P = 2.7 x 10(-11)). About 19% of affected men and 13% of the general population carry at least one copy, yielding a population attributable risk (PAR) of approximately 8%. The association was also replicated in an African American case-control group with a similar OR, in which 41% of affected individuals and 30% of the population are carriers. This leads to a greater estimated PAR (16%) that may contribute to higher incidence of prostate cancer in African American men than in men of European ancestry.     

Changes in kit fox–coyote–prey relationships in the Great Basin Desert, Utah

Variation in kit fox ( Vulpes macrotis ) population parameters can be influenced by vegetative cover and the distribution and abundance of other predator and prey species. Dramatic changes to Great Basin Desert habitats, which can potentially impact mammalian species, have occurred in some areas in Utah. We examined kit fox demographics and prey populations from 1999 to 2001 on Dugway Proving Ground (DPG), a U.S. Army facility in Utah, and compared some parameters to historical levels (1956–1958, 1966–1969). Adult survival rates were fairly consistent between 1999 and 2000 and between 1999 and 2001; however, survival was greater in 2001 than in 2000. Reproductive rates ranged from 1.0 to 3.8 pups per female in 1999–2000 and were similar to historical numbers (1.0–4.2 pups per female). We found a decrease in pre-whelping kit fox density from the 1960s (0.12 foxes ? km –2 ) to 1999–2001 (0.04 foxes ? km –2 ); however, densities were similar between the current study and the 1950s (0.08 foxes ? km –2 ). Using 9 years of data, we found density dependence between reproductive rates of the current year and annual fox density from the previous year. Using 7 years of data, we found a slight correlation between kit fox annual density and a 1-year lag in leporid abundance, even though leporid abundance was lower during the present study than it was historically. Compared to historical levels, current small mammal abundance and species composition has changed in several habitats. Kit fox breeding density and annual density were inversely correlated with coyote ( Canis latrans ) density. Changes to the landscape at DPG, especially due to invasion of cheatgrass ( Bromus tectorum ) and addition of artificial water sources, have caused a change in available kit fox habitat and prey species, and have increased the abundance of coyotes, the kit fox's major competitor.     

Bayesian inference of ancient human demography from individual genome sequences

Whole-genome sequences provide a rich source of information about human evolution. Here we describe an effort to estimate key evolutionary parameters based on the whole-genome sequences of six individuals from diverse human populations. We used a Bayesian, coalescent-based approach to obtain information about ancestral population sizes, divergence times and migration rates from inferred genealogies at many neutrally evolving loci across the genome. We introduce new methods for accommodating gene flow between populations and integrating over possible phasings of diploid genotypes. We also describe a custom pipeline for genotype inference to mitigate biases from heterogeneous sequencing technologies and coverage levels. Our analysis indicates that the San population of southern Africa diverged from other human populations approximately 108-157 thousand years ago, that Eurasians diverged from an ancestral African population 38-64 thousand years ago, and that the effective population size of the ancestors of all modern humans was ～9,000.     

Common variants at MS4A4/MS4A6E, CD2AP, CD33 and EPHA1 are associated with late-onset Alzheimer's disease

The Alzheimer Disease Genetics Consortium (ADGC) performed a genome-wide association study of late-onset Alzheimer disease using a three-stage design consisting of a discovery stage (stage 1) and two replication stages (stages 2 and 3). Both joint analysis and meta-analysis approaches were used. We obtained genome-wide significant results at MS4A4A (rs4938933; stages 1 and 2, meta-analysis P (P(M)) = 1.7 × 10(-9), joint analysis P (P(J)) = 1.7 × 10(-9); stages 1, 2 and 3, P(M) = 8.2 × 10(-12)), CD2AP (rs9349407; stages 1, 2 and 3, P(M) = 8.6 × 10(-9)), EPHA1 (rs11767557; stages 1, 2 and 3, P(M) = 6.0 × 10(-10)) and CD33 (rs3865444; stages 1, 2 and 3, P(M) = 1.6 × 10(-9)). We also replicated previous associations at CR1 (rs6701713; P(M) = 4.6 × 10(-10), P(J) = 5.2 × 10(-11)), CLU (rs1532278; P(M) = 8.3 × 10(-8), P(J) = 1.9 × 10(-8)), BIN1 (rs7561528; P(M) = 4.0 × 10(-14), P(J) = 5.2 × 10(-14)) and PICALM (rs561655; P(M) = 7.0 × 10(-11), P(J) = 1.0 × 10(-10)), but not at EXOC3L2, to late-onset Alzheimer's disease susceptibility.     

Systematic screen for human disease genes in yeast

High similarity between yeast and human mitochondria allows functional genomic study of Saccharomyces cerevisiae to be used to identify human genes involved in disease. So far, 102 heritable disorders have been attributed to defects in a quarter of the known nuclear-encoded mitochondrial proteins in humans. Many mitochondrial diseases remain unexplained, however, in part because only 40-60% of the presumed 700-1,000 proteins involved in mitochondrial function and biogenesis have been identified. Here we apply a systematic functional screen using the pre-existing whole-genome pool of yeast deletion mutants to identify mitochondrial proteins. Three million measurements of strain fitness identified 466 genes whose deletions impaired mitochondrial respiration, of which 265 were new. Our approach gave higher selection than other systematic approaches, including fivefold greater selection than gene expression analysis. To apply these advantages to human disorders involving mitochondria, human orthologs were identified and linked to heritable diseases using genomic map positions.